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README.md

@@ -2,7 +2,7 @@
 title: Stable Diffusion 3 Medium
 emoji: 🎨
 colorFrom: purple
-colorTo: indigo
+colorTo: yellow
 sdk: gradio
 sdk_version: 4.36.1
 app_file: app.py

app.py

@@ -1,18 +1,9 @@
 import gradio as gr
-import numpy as np
-import random
-import torch
-from diffusers import StableDiffusion3Pipeline
 import spaces
+from panna import SD3
 
 
-repo = "stabilityai/stable-diffusion-3-medium-diffusers"
-if torch.cuda.is_available():
-    pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=torch.float16).to("cuda")
-else:
-    pipe = StableDiffusion3Pipeline.from_pretrained(repo)
-max_seed = np.iinfo(np.int32).max
-max_image_size = 1344
+model = SD3("stabilityai/stable-diffusion-3-medium-diffusers")
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
     "An astronaut riding a green horse",
@@ -27,86 +18,40 @@ css = """
 
 
 @spaces.GPU
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-    if randomize_seed:
-        seed = random.randint(0, max_seed)
-    image = pipe(
+def infer(prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps):
+    image = model.text2image(
         prompt=prompt,
         negative_prompt=negative_prompt,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
         width=width,
         height=height,
-        generator=torch.Generator().manual_seed(seed)
-    ).images[0]
-    return image, seed
+        seed=seed
+    )
+    return image[0]
 
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown("# Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)")
         with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+            prompt = gr.Text(label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False)
             run_button = gr.Button("Run", scale=0)
         result = gr.Image(label="Result", show_label=False)
         with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative Prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-            )
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=max_seed,
-                step=1,
-                value=0,
-            )
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+            negative_prompt = gr.Text(label="Negative Prompt", max_lines=1, placeholder="Enter a negative prompt")
+            seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0)
             with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=max_image_size,
-                    step=64,
-                    value=1024,
-                )
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=max_image_size,
-                    step=64,
-                    value=1024,
-                )
+                width = gr.Slider(label="Width", minimum=256, maximum=1344, step=64, value=1024)
+                height = gr.Slider(label="Height", minimum=256, maximum=1344, step=64, value=1024)
             with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=7.5,
-                )
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=5,
-                )
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt]
-        )
+                guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=7.5)
+                num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=5)
+        gr.Examples(examples=examples, inputs=[prompt])
     gr.on(
         triggers=[run_button.click, prompt.submit, negative_prompt.submit],
         fn=infer,
-        inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        inputs=[prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps],
         outputs=[result, seed]
     )
 demo.launch()

requirements.txt

@@ -1,4 +1,3 @@
-git+https://github.com/huggingface/diffusers.git
-transformers
 accelerate
-sentencepiece
+sentencepiece
+panna